Artificial bee colony and particle swarm optimization for the estimation of nonlinear regression parameters

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Detaylı Bibliyografya
Yazarlar:	De-Los-Cobos-Silva, Sergio, Gutiérrez-Andrade, Miguel A., Rincón-García, Eric A., Lara-Velázquez, Pedro, Aguilar-Cornejo, Manuel
Materyal Türü:	artículo original
Durum:	Versión publicada
Yayın Tarihi:	2014
Diğer Bilgiler:	This paper shows the comparison results of ABC (Artificial Bee Colony) and PSO (Particle Swarm Optimization) heuristic tech- niques that were used to estimate parameters for nonlinear regression models. The algorithms were tested on 27 data bases from the NIST collection (2001), 8 of these are considered to have high difficulty, 11 medium difficulty and 8 low difficulty. Experimental results are presented.
Ülke:	Portal de Revistas UCR
Kurum:	Universidad de Costa Rica
Repositorio:	Portal de Revistas UCR
Dil:	Español
OAI Identifier:	oai:archivo.portal.ucr.ac.cr:article/14141
Online Erişim:	https://archivo.revistas.ucr.ac.cr/index.php/matematica/article/view/14141
Anahtar Kelime:	artificial bee colony particle swarm optimization nonlinear regression colonias de abejas artificiales enjambres de partículas regresión no lineal